An epidemiological early warning system for COVID-19 dynamics
 
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Division for Digital Medicine and Telehealth, UMIT Tirol - Private University for Health Sciences and Health Technology, Tyrol, Austria
 
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Tyrolean Federal Institute for Integrated Care, Tirol Kliniken GmbH, Innsbruck, Austria
 
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Division for Digital Medicine and Telehealth, Private University for Health Sciences and Health Technology (UMIT Tirol), Hall, Austria
 
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Division for Digital Medicine and Telehealth, UMIT TIROL - Private University for Health Sciences and Health Technology, Hall (Tyrol), Austria
 
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Division for Digital Medicine and Telehealth, UMIT TIROL, Private University for Health Sciences and Health Technology, Tyrol, Austria
 
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(UMIT TIROL), Private University for Health Sciences and Health Technology, Tyrol, Austria
 
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Institute of Legal Medicine and Core Facility Metabolomics, Medical University of Innsbruck, Innsbruck, Austria
 
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Central Institute for Blood Transfusion and Immunology, Tirol Kliniken GmbH, Innsbruck, Austria
 
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Department of Internal Medicine I, Medical University of Innsbruck, Innsbruck, Austria.
 
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Division for Digital Medicine and Telehealth, UMIT TIROL, Private University for Health Sciences and Health Technology, Hall (Tyrol), Austria and Tyrolean Federal Institute for Integrated Care, Tirol Kliniken GmbH, Innsbruck, Austria
 
 
Publication date: 2023-04-27
 
 
Popul. Med. 2023;5(Supplement):A1920
 
ABSTRACT
Background and Objective: Infectious diseases as well as infectious disease control measures have a huge impact on healthcare, social life and economy. Therefore, measures have to be adopted in a very considerate manner. In order to support COVID-19 control management in the Austrian province Tyrol the Epidemiological Early Warning System (EEWS) was implemented and is presented in this abstract. Methods: The EEWS of the Austrian province Tyrol is based on three pillars: (1) An agent-based simulation package named “surviral” was developed. (2) Wastewater from all Tyrolean wastewater treatment plants is analyzed. (2) COVID-19 antibodies of healthy blood donors are determined. Results: The Austrian province Tyrol implemented an EEWS in order to adopt control measures, such as social distancing, quarantines, curfews or lockdowns based on an accurate model. The model integrates parameters including number of known infections, number of vaccinations, circulating virus variants to provide a 10-day forecast of hospitalization rates (standard and intensive care) for Tyrol and South Tyrol. Additionally, the model is parametrized using information regarding the wastewater virus load and blood donor antibodies. The overall accuracy was about 1.5% average error. However, EEWS does not only simulate the dynamics of the COVID-19 pandemic on the federal state level, but also on the district and municipal level. Thus, disease control measures can be adopted exactly where needed instead of affecting the entire province. Conclusions: The crisis team of the Austrian province of Tyrol uses the Tyrolean EEWS, which is a very accurate model. It supports decision-makers with a solid information base regarding the dynamics of the pandemic. In future, the EEWS can be used for various infectious diseases and thus be a basis for infectious disease monitoring.
ISSN:2654-1459
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